Intelligent evaluation of strabismus in videos based on an automated cover test

Yang Zheng, Hong Fu, Ruimin Li, Wai Lun Lo, Zheru Chi, David Dagan Feng, Zongxi Song, Desheng Wen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)


Strabismus is a common vision disease that brings about unpleasant influence on vision, as well as life quality. A timely diagnosis is crucial for the proper treatment of strabismus. In contrast to manual evaluation, well-designed automatic evaluation can significantly improve the objectivity, reliability, and efficiency of strabismus diagnosis. In this study, we have proposed an innovative intelligent evaluation system of strabismus in digital videos, based on the cover test. In particular, the video is recorded using an infrared camera, while the subject performs automated cover tests. The video is then fed into the proposed algorithm that consists of six stages: (1) eye region extraction, (2) iris boundary detection, (3) key frame detection, (4) pupil localization, (5) deviation calculation, and (6) evaluation of strabismus. A database containing cover test data of both strabismic subjects and normal subjects was established for experiments. Experimental results demonstrate that the deviation of strabismus can be well-evaluated by our proposed method. The accuracy was over 91%, in the horizontal direction, with an error of 8 diopters; and it was over 86% in the vertical direction, with an error of 4 diopters.

Original languageEnglish
Article number731
JournalApplied Sciences (Switzerland)
Issue number4
Publication statusPublished - 20 Feb 2019


  • Automated cover tests
  • Deviation of strabismus
  • Intelligent evaluation
  • Pupil localization

ASJC Scopus subject areas

  • General Materials Science
  • Instrumentation
  • General Engineering
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes


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